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  <div class="section" id="named-tensors-operator-coverage">
<span id="name-inference-reference-doc"></span><h1>Named Tensors operator coverage<a class="headerlink" href="#named-tensors-operator-coverage" title="Permalink to this headline">¶</a></h1>
<p>Please read <a class="reference internal" href="named_tensor.html#named-tensors-doc"><span class="std std-ref">Named Tensors</span></a> first for an introduction to named tensors.</p>
<p>This document is a reference for <em>name inference</em>, a process that defines how
named tensors:</p>
<ol class="arabic simple">
<li><p>use names to provide additional automatic runtime correctness checks</p></li>
<li><p>propagate names from input tensors to output tensors</p></li>
</ol>
<p>Below is a list of all operations that are supported with named tensors
and their associated name inference rules.</p>
<p>If you don’t see an operation listed here, but it would help your use case, please
<a class="reference external" href="https://github.com/pytorch/pytorch/issues?q=is%3Aopen+is%3Aissue+label%3A%22module%3A+named+tensor%22">search if an issue has already been filed</a> and if not, <a class="reference external" href="https://github.com/pytorch/pytorch/issues/new/choose">file one</a>.</p>
<div class="admonition warning">
<p class="admonition-title">Warning</p>
<p>The named tensor API is experimental and subject to change.</p>
</div>
<table class="colwidths-given docutils align-default" id="id1">
<caption><span class="caption-text">Supported Operations</span><a class="headerlink" href="#id1" title="Permalink to this table">¶</a></caption>
<colgroup>
<col style="width: 50%" />
<col style="width: 50%" />
</colgroup>
<thead>
<tr class="row-odd"><th class="head"><p>API</p></th>
<th class="head"><p>Name inference rule</p></th>
</tr>
</thead>
<tbody>
<tr class="row-even"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.abs" title="torch.Tensor.abs"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.abs()</span></code></a>, <a class="reference internal" href="torch.html#torch.abs" title="torch.abs"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.abs()</span></code></a></p></td>
<td><p><a class="reference internal" href="#keeps-input-names-doc"><span class="std std-ref">Keeps input names</span></a></p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.abs_" title="torch.Tensor.abs_"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.abs_()</span></code></a></p></td>
<td><p><a class="reference internal" href="#keeps-input-names-doc"><span class="std std-ref">Keeps input names</span></a></p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.acos" title="torch.Tensor.acos"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.acos()</span></code></a>, <a class="reference internal" href="torch.html#torch.acos" title="torch.acos"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.acos()</span></code></a></p></td>
<td><p><a class="reference internal" href="#keeps-input-names-doc"><span class="std std-ref">Keeps input names</span></a></p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.acos_" title="torch.Tensor.acos_"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.acos_()</span></code></a></p></td>
<td><p><a class="reference internal" href="#keeps-input-names-doc"><span class="std std-ref">Keeps input names</span></a></p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.add" title="torch.Tensor.add"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.add()</span></code></a>, <a class="reference internal" href="torch.html#torch.add" title="torch.add"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.add()</span></code></a></p></td>
<td><p><a class="reference internal" href="#unifies-names-from-inputs-doc"><span class="std std-ref">Unifies names from inputs</span></a></p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.add_" title="torch.Tensor.add_"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.add_()</span></code></a></p></td>
<td><p><a class="reference internal" href="#unifies-names-from-inputs-doc"><span class="std std-ref">Unifies names from inputs</span></a></p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.addmm" title="torch.Tensor.addmm"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.addmm()</span></code></a>, <a class="reference internal" href="torch.html#torch.addmm" title="torch.addmm"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.addmm()</span></code></a></p></td>
<td><p><a class="reference internal" href="#contracts-away-dims-doc"><span class="std std-ref">Contracts away dims</span></a></p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.addmm_" title="torch.Tensor.addmm_"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.addmm_()</span></code></a></p></td>
<td><p><a class="reference internal" href="#contracts-away-dims-doc"><span class="std std-ref">Contracts away dims</span></a></p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.addmv" title="torch.Tensor.addmv"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.addmv()</span></code></a>, <a class="reference internal" href="torch.html#torch.addmv" title="torch.addmv"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.addmv()</span></code></a></p></td>
<td><p><a class="reference internal" href="#contracts-away-dims-doc"><span class="std std-ref">Contracts away dims</span></a></p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.addmv_" title="torch.Tensor.addmv_"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.addmv_()</span></code></a></p></td>
<td><p><a class="reference internal" href="#contracts-away-dims-doc"><span class="std std-ref">Contracts away dims</span></a></p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="named_tensor.html#torch.Tensor.align_as" title="torch.Tensor.align_as"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.align_as()</span></code></a></p></td>
<td><p>See documentation</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="named_tensor.html#torch.Tensor.align_to" title="torch.Tensor.align_to"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.align_to()</span></code></a></p></td>
<td><p>See documentation</p></td>
</tr>
<tr class="row-even"><td><p><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.all()</span></code>, <code class="xref py py-func docutils literal notranslate"><span class="pre">torch.all()</span></code></p></td>
<td><p>None</p></td>
</tr>
<tr class="row-odd"><td><p><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.any()</span></code>, <code class="xref py py-func docutils literal notranslate"><span class="pre">torch.any()</span></code></p></td>
<td><p>None</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.asin" title="torch.Tensor.asin"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.asin()</span></code></a>, <a class="reference internal" href="torch.html#torch.asin" title="torch.asin"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.asin()</span></code></a></p></td>
<td><p><a class="reference internal" href="#keeps-input-names-doc"><span class="std std-ref">Keeps input names</span></a></p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.asin_" title="torch.Tensor.asin_"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.asin_()</span></code></a></p></td>
<td><p><a class="reference internal" href="#keeps-input-names-doc"><span class="std std-ref">Keeps input names</span></a></p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.atan" title="torch.Tensor.atan"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.atan()</span></code></a>, <a class="reference internal" href="torch.html#torch.atan" title="torch.atan"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.atan()</span></code></a></p></td>
<td><p><a class="reference internal" href="#keeps-input-names-doc"><span class="std std-ref">Keeps input names</span></a></p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.atan2" title="torch.Tensor.atan2"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.atan2()</span></code></a>, <a class="reference internal" href="torch.html#torch.atan2" title="torch.atan2"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.atan2()</span></code></a></p></td>
<td><p><a class="reference internal" href="#unifies-names-from-inputs-doc"><span class="std std-ref">Unifies names from inputs</span></a></p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.atan2_" title="torch.Tensor.atan2_"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.atan2_()</span></code></a></p></td>
<td><p><a class="reference internal" href="#unifies-names-from-inputs-doc"><span class="std std-ref">Unifies names from inputs</span></a></p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.atan_" title="torch.Tensor.atan_"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.atan_()</span></code></a></p></td>
<td><p><a class="reference internal" href="#keeps-input-names-doc"><span class="std std-ref">Keeps input names</span></a></p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.bernoulli" title="torch.Tensor.bernoulli"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.bernoulli()</span></code></a>, <a class="reference internal" href="torch.html#torch.bernoulli" title="torch.bernoulli"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.bernoulli()</span></code></a></p></td>
<td><p><a class="reference internal" href="#keeps-input-names-doc"><span class="std std-ref">Keeps input names</span></a></p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.bernoulli_" title="torch.Tensor.bernoulli_"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.bernoulli_()</span></code></a></p></td>
<td><p>None</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.bfloat16" title="torch.Tensor.bfloat16"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.bfloat16()</span></code></a></p></td>
<td><p><a class="reference internal" href="#keeps-input-names-doc"><span class="std std-ref">Keeps input names</span></a></p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.bitwise_not" title="torch.Tensor.bitwise_not"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.bitwise_not()</span></code></a>, <a class="reference internal" href="torch.html#torch.bitwise_not" title="torch.bitwise_not"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.bitwise_not()</span></code></a></p></td>
<td><p><a class="reference internal" href="#keeps-input-names-doc"><span class="std std-ref">Keeps input names</span></a></p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.bitwise_not_" title="torch.Tensor.bitwise_not_"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.bitwise_not_()</span></code></a></p></td>
<td><p>None</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.bmm" title="torch.Tensor.bmm"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.bmm()</span></code></a>, <a class="reference internal" href="torch.html#torch.bmm" title="torch.bmm"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.bmm()</span></code></a></p></td>
<td><p><a class="reference internal" href="#contracts-away-dims-doc"><span class="std std-ref">Contracts away dims</span></a></p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.bool" title="torch.Tensor.bool"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.bool()</span></code></a></p></td>
<td><p><a class="reference internal" href="#keeps-input-names-doc"><span class="std std-ref">Keeps input names</span></a></p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.byte" title="torch.Tensor.byte"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.byte()</span></code></a></p></td>
<td><p><a class="reference internal" href="#keeps-input-names-doc"><span class="std std-ref">Keeps input names</span></a></p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="torch.html#torch.cat" title="torch.cat"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.cat()</span></code></a></p></td>
<td><p><a class="reference internal" href="#unifies-names-from-inputs-doc"><span class="std std-ref">Unifies names from inputs</span></a></p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.cauchy_" title="torch.Tensor.cauchy_"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.cauchy_()</span></code></a></p></td>
<td><p>None</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.ceil" title="torch.Tensor.ceil"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.ceil()</span></code></a>, <a class="reference internal" href="torch.html#torch.ceil" title="torch.ceil"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.ceil()</span></code></a></p></td>
<td><p><a class="reference internal" href="#keeps-input-names-doc"><span class="std std-ref">Keeps input names</span></a></p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.ceil_" title="torch.Tensor.ceil_"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.ceil_()</span></code></a></p></td>
<td><p>None</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.char" title="torch.Tensor.char"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.char()</span></code></a></p></td>
<td><p><a class="reference internal" href="#keeps-input-names-doc"><span class="std std-ref">Keeps input names</span></a></p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.chunk" title="torch.Tensor.chunk"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.chunk()</span></code></a>, <a class="reference internal" href="torch.html#torch.chunk" title="torch.chunk"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.chunk()</span></code></a></p></td>
<td><p><a class="reference internal" href="#keeps-input-names-doc"><span class="std std-ref">Keeps input names</span></a></p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.clamp" title="torch.Tensor.clamp"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.clamp()</span></code></a>, <a class="reference internal" href="torch.html#torch.clamp" title="torch.clamp"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.clamp()</span></code></a></p></td>
<td><p><a class="reference internal" href="#keeps-input-names-doc"><span class="std std-ref">Keeps input names</span></a></p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.clamp_" title="torch.Tensor.clamp_"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.clamp_()</span></code></a></p></td>
<td><p>None</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.copy_" title="torch.Tensor.copy_"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.copy_()</span></code></a></p></td>
<td><p><a class="reference internal" href="#out-function-semantics-doc"><span class="std std-ref">out function and in-place variants</span></a></p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.cos" title="torch.Tensor.cos"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.cos()</span></code></a>, <a class="reference internal" href="torch.html#torch.cos" title="torch.cos"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.cos()</span></code></a></p></td>
<td><p><a class="reference internal" href="#keeps-input-names-doc"><span class="std std-ref">Keeps input names</span></a></p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.cos_" title="torch.Tensor.cos_"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.cos_()</span></code></a></p></td>
<td><p>None</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.cosh" title="torch.Tensor.cosh"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.cosh()</span></code></a>, <a class="reference internal" href="torch.html#torch.cosh" title="torch.cosh"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.cosh()</span></code></a></p></td>
<td><p><a class="reference internal" href="#keeps-input-names-doc"><span class="std std-ref">Keeps input names</span></a></p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.cosh_" title="torch.Tensor.cosh_"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.cosh_()</span></code></a></p></td>
<td><p>None</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.cpu" title="torch.Tensor.cpu"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.cpu()</span></code></a></p></td>
<td><p><a class="reference internal" href="#keeps-input-names-doc"><span class="std std-ref">Keeps input names</span></a></p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.cuda" title="torch.Tensor.cuda"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.cuda()</span></code></a></p></td>
<td><p><a class="reference internal" href="#keeps-input-names-doc"><span class="std std-ref">Keeps input names</span></a></p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.cumprod" title="torch.Tensor.cumprod"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.cumprod()</span></code></a>, <a class="reference internal" href="torch.html#torch.cumprod" title="torch.cumprod"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.cumprod()</span></code></a></p></td>
<td><p><a class="reference internal" href="#keeps-input-names-doc"><span class="std std-ref">Keeps input names</span></a></p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.cumsum" title="torch.Tensor.cumsum"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.cumsum()</span></code></a>, <a class="reference internal" href="torch.html#torch.cumsum" title="torch.cumsum"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.cumsum()</span></code></a></p></td>
<td><p><a class="reference internal" href="#keeps-input-names-doc"><span class="std std-ref">Keeps input names</span></a></p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.data_ptr" title="torch.Tensor.data_ptr"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.data_ptr()</span></code></a></p></td>
<td><p>None</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="autograd.html#torch.Tensor.detach" title="torch.Tensor.detach"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.detach()</span></code></a>, <code class="xref py py-func docutils literal notranslate"><span class="pre">torch.detach()</span></code></p></td>
<td><p><a class="reference internal" href="#keeps-input-names-doc"><span class="std std-ref">Keeps input names</span></a></p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="autograd.html#torch.Tensor.detach_" title="torch.Tensor.detach_"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.detach_()</span></code></a></p></td>
<td><p>None</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.device" title="torch.Tensor.device"><code class="xref py py-attr docutils literal notranslate"><span class="pre">Tensor.device</span></code></a>, <a class="reference internal" href="tensor_attributes.html#torch.torch.device" title="torch.torch.device"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.device()</span></code></a></p></td>
<td><p>None</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.digamma" title="torch.Tensor.digamma"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.digamma()</span></code></a>, <a class="reference internal" href="torch.html#torch.digamma" title="torch.digamma"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.digamma()</span></code></a></p></td>
<td><p><a class="reference internal" href="#keeps-input-names-doc"><span class="std std-ref">Keeps input names</span></a></p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.digamma_" title="torch.Tensor.digamma_"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.digamma_()</span></code></a></p></td>
<td><p>None</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.dim" title="torch.Tensor.dim"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.dim()</span></code></a></p></td>
<td><p>None</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.div" title="torch.Tensor.div"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.div()</span></code></a>, <a class="reference internal" href="torch.html#torch.div" title="torch.div"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.div()</span></code></a></p></td>
<td><p><a class="reference internal" href="#unifies-names-from-inputs-doc"><span class="std std-ref">Unifies names from inputs</span></a></p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.div_" title="torch.Tensor.div_"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.div_()</span></code></a></p></td>
<td><p><a class="reference internal" href="#unifies-names-from-inputs-doc"><span class="std std-ref">Unifies names from inputs</span></a></p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.dot" title="torch.Tensor.dot"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.dot()</span></code></a>, <a class="reference internal" href="torch.html#torch.dot" title="torch.dot"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.dot()</span></code></a></p></td>
<td><p>None</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.double" title="torch.Tensor.double"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.double()</span></code></a></p></td>
<td><p><a class="reference internal" href="#keeps-input-names-doc"><span class="std std-ref">Keeps input names</span></a></p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.element_size" title="torch.Tensor.element_size"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.element_size()</span></code></a></p></td>
<td><p>None</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="torch.html#torch.empty" title="torch.empty"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.empty()</span></code></a></p></td>
<td><p><a class="reference internal" href="#factory-doc"><span class="std std-ref">Factory functions</span></a></p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="torch.html#torch.empty_like" title="torch.empty_like"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.empty_like()</span></code></a></p></td>
<td><p><a class="reference internal" href="#factory-doc"><span class="std std-ref">Factory functions</span></a></p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.eq" title="torch.Tensor.eq"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.eq()</span></code></a>, <a class="reference internal" href="torch.html#torch.eq" title="torch.eq"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.eq()</span></code></a></p></td>
<td><p><a class="reference internal" href="#unifies-names-from-inputs-doc"><span class="std std-ref">Unifies names from inputs</span></a></p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.erf" title="torch.Tensor.erf"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.erf()</span></code></a>, <a class="reference internal" href="torch.html#torch.erf" title="torch.erf"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.erf()</span></code></a></p></td>
<td><p><a class="reference internal" href="#keeps-input-names-doc"><span class="std std-ref">Keeps input names</span></a></p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.erf_" title="torch.Tensor.erf_"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.erf_()</span></code></a></p></td>
<td><p>None</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.erfc" title="torch.Tensor.erfc"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.erfc()</span></code></a>, <a class="reference internal" href="torch.html#torch.erfc" title="torch.erfc"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.erfc()</span></code></a></p></td>
<td><p><a class="reference internal" href="#keeps-input-names-doc"><span class="std std-ref">Keeps input names</span></a></p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.erfc_" title="torch.Tensor.erfc_"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.erfc_()</span></code></a></p></td>
<td><p>None</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.erfinv" title="torch.Tensor.erfinv"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.erfinv()</span></code></a>, <a class="reference internal" href="torch.html#torch.erfinv" title="torch.erfinv"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.erfinv()</span></code></a></p></td>
<td><p><a class="reference internal" href="#keeps-input-names-doc"><span class="std std-ref">Keeps input names</span></a></p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.erfinv_" title="torch.Tensor.erfinv_"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.erfinv_()</span></code></a></p></td>
<td><p>None</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.exp" title="torch.Tensor.exp"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.exp()</span></code></a>, <a class="reference internal" href="torch.html#torch.exp" title="torch.exp"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.exp()</span></code></a></p></td>
<td><p><a class="reference internal" href="#keeps-input-names-doc"><span class="std std-ref">Keeps input names</span></a></p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.exp_" title="torch.Tensor.exp_"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.exp_()</span></code></a></p></td>
<td><p>None</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.expand" title="torch.Tensor.expand"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.expand()</span></code></a></p></td>
<td><p><a class="reference internal" href="#keeps-input-names-doc"><span class="std std-ref">Keeps input names</span></a></p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.expm1" title="torch.Tensor.expm1"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.expm1()</span></code></a>, <a class="reference internal" href="torch.html#torch.expm1" title="torch.expm1"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.expm1()</span></code></a></p></td>
<td><p><a class="reference internal" href="#keeps-input-names-doc"><span class="std std-ref">Keeps input names</span></a></p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.expm1_" title="torch.Tensor.expm1_"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.expm1_()</span></code></a></p></td>
<td><p>None</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.exponential_" title="torch.Tensor.exponential_"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.exponential_()</span></code></a></p></td>
<td><p>None</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.fill_" title="torch.Tensor.fill_"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.fill_()</span></code></a></p></td>
<td><p>None</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.flatten" title="torch.Tensor.flatten"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.flatten()</span></code></a>, <a class="reference internal" href="torch.html#torch.flatten" title="torch.flatten"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.flatten()</span></code></a></p></td>
<td><p>See documentation</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.float" title="torch.Tensor.float"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.float()</span></code></a></p></td>
<td><p><a class="reference internal" href="#keeps-input-names-doc"><span class="std std-ref">Keeps input names</span></a></p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.floor" title="torch.Tensor.floor"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.floor()</span></code></a>, <a class="reference internal" href="torch.html#torch.floor" title="torch.floor"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.floor()</span></code></a></p></td>
<td><p><a class="reference internal" href="#keeps-input-names-doc"><span class="std std-ref">Keeps input names</span></a></p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.floor_" title="torch.Tensor.floor_"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.floor_()</span></code></a></p></td>
<td><p>None</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.frac" title="torch.Tensor.frac"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.frac()</span></code></a>, <a class="reference internal" href="torch.html#torch.frac" title="torch.frac"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.frac()</span></code></a></p></td>
<td><p><a class="reference internal" href="#keeps-input-names-doc"><span class="std std-ref">Keeps input names</span></a></p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.frac_" title="torch.Tensor.frac_"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.frac_()</span></code></a></p></td>
<td><p>None</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.ge" title="torch.Tensor.ge"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.ge()</span></code></a>, <a class="reference internal" href="torch.html#torch.ge" title="torch.ge"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.ge()</span></code></a></p></td>
<td><p><a class="reference internal" href="#unifies-names-from-inputs-doc"><span class="std std-ref">Unifies names from inputs</span></a></p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.get_device" title="torch.Tensor.get_device"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.get_device()</span></code></a>, <code class="xref py py-func docutils literal notranslate"><span class="pre">torch.get_device()</span></code></p></td>
<td><p>None</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="autograd.html#torch.Tensor.grad" title="torch.Tensor.grad"><code class="xref py py-attr docutils literal notranslate"><span class="pre">Tensor.grad</span></code></a></p></td>
<td><p>None</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.gt" title="torch.Tensor.gt"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.gt()</span></code></a>, <a class="reference internal" href="torch.html#torch.gt" title="torch.gt"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.gt()</span></code></a></p></td>
<td><p><a class="reference internal" href="#unifies-names-from-inputs-doc"><span class="std std-ref">Unifies names from inputs</span></a></p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.half" title="torch.Tensor.half"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.half()</span></code></a></p></td>
<td><p><a class="reference internal" href="#keeps-input-names-doc"><span class="std std-ref">Keeps input names</span></a></p></td>
</tr>
<tr class="row-even"><td><p><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.has_names()</span></code></p></td>
<td><p>See documentation</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.index_fill" title="torch.Tensor.index_fill"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.index_fill()</span></code></a>, <code class="xref py py-func docutils literal notranslate"><span class="pre">torch.index_fill()</span></code></p></td>
<td><p><a class="reference internal" href="#keeps-input-names-doc"><span class="std std-ref">Keeps input names</span></a></p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.index_fill_" title="torch.Tensor.index_fill_"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.index_fill_()</span></code></a></p></td>
<td><p>None</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.int" title="torch.Tensor.int"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.int()</span></code></a></p></td>
<td><p><a class="reference internal" href="#keeps-input-names-doc"><span class="std std-ref">Keeps input names</span></a></p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.is_contiguous" title="torch.Tensor.is_contiguous"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.is_contiguous()</span></code></a></p></td>
<td><p>None</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.is_cuda" title="torch.Tensor.is_cuda"><code class="xref py py-attr docutils literal notranslate"><span class="pre">Tensor.is_cuda</span></code></a></p></td>
<td><p>None</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.is_floating_point" title="torch.Tensor.is_floating_point"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.is_floating_point()</span></code></a>, <a class="reference internal" href="torch.html#torch.is_floating_point" title="torch.is_floating_point"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.is_floating_point()</span></code></a></p></td>
<td><p>None</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="autograd.html#torch.Tensor.is_leaf" title="torch.Tensor.is_leaf"><code class="xref py py-attr docutils literal notranslate"><span class="pre">Tensor.is_leaf</span></code></a></p></td>
<td><p>None</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.is_pinned" title="torch.Tensor.is_pinned"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.is_pinned()</span></code></a></p></td>
<td><p>None</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.is_shared" title="torch.Tensor.is_shared"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.is_shared()</span></code></a></p></td>
<td><p>None</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.is_signed" title="torch.Tensor.is_signed"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.is_signed()</span></code></a>, <code class="xref py py-func docutils literal notranslate"><span class="pre">torch.is_signed()</span></code></p></td>
<td><p>None</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.is_sparse" title="torch.Tensor.is_sparse"><code class="xref py py-attr docutils literal notranslate"><span class="pre">Tensor.is_sparse</span></code></a></p></td>
<td><p>None</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="torch.html#torch.is_tensor" title="torch.is_tensor"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.is_tensor()</span></code></a></p></td>
<td><p>None</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.item" title="torch.Tensor.item"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.item()</span></code></a></p></td>
<td><p>None</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.kthvalue" title="torch.Tensor.kthvalue"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.kthvalue()</span></code></a>, <a class="reference internal" href="torch.html#torch.kthvalue" title="torch.kthvalue"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.kthvalue()</span></code></a></p></td>
<td><p><a class="reference internal" href="#removes-dimensions-doc"><span class="std std-ref">Removes dimensions</span></a></p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.le" title="torch.Tensor.le"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.le()</span></code></a>, <a class="reference internal" href="torch.html#torch.le" title="torch.le"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.le()</span></code></a></p></td>
<td><p><a class="reference internal" href="#unifies-names-from-inputs-doc"><span class="std std-ref">Unifies names from inputs</span></a></p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.log" title="torch.Tensor.log"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.log()</span></code></a>, <a class="reference internal" href="torch.html#torch.log" title="torch.log"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.log()</span></code></a></p></td>
<td><p><a class="reference internal" href="#keeps-input-names-doc"><span class="std std-ref">Keeps input names</span></a></p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.log10" title="torch.Tensor.log10"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.log10()</span></code></a>, <a class="reference internal" href="torch.html#torch.log10" title="torch.log10"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.log10()</span></code></a></p></td>
<td><p><a class="reference internal" href="#keeps-input-names-doc"><span class="std std-ref">Keeps input names</span></a></p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.log10_" title="torch.Tensor.log10_"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.log10_()</span></code></a></p></td>
<td><p>None</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.log1p" title="torch.Tensor.log1p"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.log1p()</span></code></a>, <a class="reference internal" href="torch.html#torch.log1p" title="torch.log1p"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.log1p()</span></code></a></p></td>
<td><p><a class="reference internal" href="#keeps-input-names-doc"><span class="std std-ref">Keeps input names</span></a></p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.log1p_" title="torch.Tensor.log1p_"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.log1p_()</span></code></a></p></td>
<td><p>None</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.log2" title="torch.Tensor.log2"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.log2()</span></code></a>, <a class="reference internal" href="torch.html#torch.log2" title="torch.log2"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.log2()</span></code></a></p></td>
<td><p><a class="reference internal" href="#keeps-input-names-doc"><span class="std std-ref">Keeps input names</span></a></p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.log2_" title="torch.Tensor.log2_"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.log2_()</span></code></a></p></td>
<td><p>None</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.log_" title="torch.Tensor.log_"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.log_()</span></code></a></p></td>
<td><p>None</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.log_normal_" title="torch.Tensor.log_normal_"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.log_normal_()</span></code></a></p></td>
<td><p>None</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.logical_not" title="torch.Tensor.logical_not"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.logical_not()</span></code></a>, <a class="reference internal" href="torch.html#torch.logical_not" title="torch.logical_not"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.logical_not()</span></code></a></p></td>
<td><p><a class="reference internal" href="#keeps-input-names-doc"><span class="std std-ref">Keeps input names</span></a></p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.logical_not_" title="torch.Tensor.logical_not_"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.logical_not_()</span></code></a></p></td>
<td><p>None</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.logsumexp" title="torch.Tensor.logsumexp"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.logsumexp()</span></code></a>, <a class="reference internal" href="torch.html#torch.logsumexp" title="torch.logsumexp"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.logsumexp()</span></code></a></p></td>
<td><p><a class="reference internal" href="#removes-dimensions-doc"><span class="std std-ref">Removes dimensions</span></a></p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.long" title="torch.Tensor.long"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.long()</span></code></a></p></td>
<td><p><a class="reference internal" href="#keeps-input-names-doc"><span class="std std-ref">Keeps input names</span></a></p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.lt" title="torch.Tensor.lt"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.lt()</span></code></a>, <a class="reference internal" href="torch.html#torch.lt" title="torch.lt"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.lt()</span></code></a></p></td>
<td><p><a class="reference internal" href="#unifies-names-from-inputs-doc"><span class="std std-ref">Unifies names from inputs</span></a></p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="torch.html#torch.manual_seed" title="torch.manual_seed"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.manual_seed()</span></code></a></p></td>
<td><p>None</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.masked_fill" title="torch.Tensor.masked_fill"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.masked_fill()</span></code></a>, <code class="xref py py-func docutils literal notranslate"><span class="pre">torch.masked_fill()</span></code></p></td>
<td><p><a class="reference internal" href="#keeps-input-names-doc"><span class="std std-ref">Keeps input names</span></a></p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.masked_fill_" title="torch.Tensor.masked_fill_"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.masked_fill_()</span></code></a></p></td>
<td><p>None</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.masked_select" title="torch.Tensor.masked_select"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.masked_select()</span></code></a>, <a class="reference internal" href="torch.html#torch.masked_select" title="torch.masked_select"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.masked_select()</span></code></a></p></td>
<td><p>Aligns mask up to input and then unifies_names_from_input_tensors</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.matmul" title="torch.Tensor.matmul"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.matmul()</span></code></a>, <a class="reference internal" href="torch.html#torch.matmul" title="torch.matmul"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.matmul()</span></code></a></p></td>
<td><p><a class="reference internal" href="#contracts-away-dims-doc"><span class="std std-ref">Contracts away dims</span></a></p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.mean" title="torch.Tensor.mean"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.mean()</span></code></a>, <a class="reference internal" href="torch.html#torch.mean" title="torch.mean"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.mean()</span></code></a></p></td>
<td><p><a class="reference internal" href="#removes-dimensions-doc"><span class="std std-ref">Removes dimensions</span></a></p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.median" title="torch.Tensor.median"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.median()</span></code></a>, <a class="reference internal" href="torch.html#torch.median" title="torch.median"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.median()</span></code></a></p></td>
<td><p><a class="reference internal" href="#removes-dimensions-doc"><span class="std std-ref">Removes dimensions</span></a></p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.mm" title="torch.Tensor.mm"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.mm()</span></code></a>, <a class="reference internal" href="torch.html#torch.mm" title="torch.mm"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.mm()</span></code></a></p></td>
<td><p><a class="reference internal" href="#contracts-away-dims-doc"><span class="std std-ref">Contracts away dims</span></a></p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.mode" title="torch.Tensor.mode"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.mode()</span></code></a>, <a class="reference internal" href="torch.html#torch.mode" title="torch.mode"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.mode()</span></code></a></p></td>
<td><p><a class="reference internal" href="#removes-dimensions-doc"><span class="std std-ref">Removes dimensions</span></a></p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.mul" title="torch.Tensor.mul"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.mul()</span></code></a>, <a class="reference internal" href="torch.html#torch.mul" title="torch.mul"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.mul()</span></code></a></p></td>
<td><p><a class="reference internal" href="#unifies-names-from-inputs-doc"><span class="std std-ref">Unifies names from inputs</span></a></p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.mul_" title="torch.Tensor.mul_"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.mul_()</span></code></a></p></td>
<td><p><a class="reference internal" href="#unifies-names-from-inputs-doc"><span class="std std-ref">Unifies names from inputs</span></a></p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.mv" title="torch.Tensor.mv"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.mv()</span></code></a>, <a class="reference internal" href="torch.html#torch.mv" title="torch.mv"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.mv()</span></code></a></p></td>
<td><p><a class="reference internal" href="#contracts-away-dims-doc"><span class="std std-ref">Contracts away dims</span></a></p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="named_tensor.html#torch.Tensor.names" title="torch.Tensor.names"><code class="xref py py-attr docutils literal notranslate"><span class="pre">Tensor.names</span></code></a></p></td>
<td><p>See documentation</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.narrow" title="torch.Tensor.narrow"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.narrow()</span></code></a>, <a class="reference internal" href="torch.html#torch.narrow" title="torch.narrow"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.narrow()</span></code></a></p></td>
<td><p><a class="reference internal" href="#keeps-input-names-doc"><span class="std std-ref">Keeps input names</span></a></p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.ndim" title="torch.Tensor.ndim"><code class="xref py py-attr docutils literal notranslate"><span class="pre">Tensor.ndim</span></code></a></p></td>
<td><p>None</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.ndimension" title="torch.Tensor.ndimension"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.ndimension()</span></code></a></p></td>
<td><p>None</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.ne" title="torch.Tensor.ne"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.ne()</span></code></a>, <a class="reference internal" href="torch.html#torch.ne" title="torch.ne"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.ne()</span></code></a></p></td>
<td><p><a class="reference internal" href="#unifies-names-from-inputs-doc"><span class="std std-ref">Unifies names from inputs</span></a></p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.neg" title="torch.Tensor.neg"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.neg()</span></code></a>, <a class="reference internal" href="torch.html#torch.neg" title="torch.neg"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.neg()</span></code></a></p></td>
<td><p><a class="reference internal" href="#keeps-input-names-doc"><span class="std std-ref">Keeps input names</span></a></p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.neg_" title="torch.Tensor.neg_"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.neg_()</span></code></a></p></td>
<td><p>None</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="torch.html#torch.normal" title="torch.normal"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.normal()</span></code></a></p></td>
<td><p><a class="reference internal" href="#keeps-input-names-doc"><span class="std std-ref">Keeps input names</span></a></p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.normal_" title="torch.Tensor.normal_"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.normal_()</span></code></a></p></td>
<td><p>None</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.numel" title="torch.Tensor.numel"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.numel()</span></code></a>, <a class="reference internal" href="torch.html#torch.numel" title="torch.numel"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.numel()</span></code></a></p></td>
<td><p>None</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="torch.html#torch.ones" title="torch.ones"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.ones()</span></code></a></p></td>
<td><p><a class="reference internal" href="#factory-doc"><span class="std std-ref">Factory functions</span></a></p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.pow" title="torch.Tensor.pow"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.pow()</span></code></a>, <a class="reference internal" href="torch.html#torch.pow" title="torch.pow"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.pow()</span></code></a></p></td>
<td><p><a class="reference internal" href="#unifies-names-from-inputs-doc"><span class="std std-ref">Unifies names from inputs</span></a></p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.pow_" title="torch.Tensor.pow_"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.pow_()</span></code></a></p></td>
<td><p>None</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.prod" title="torch.Tensor.prod"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.prod()</span></code></a>, <a class="reference internal" href="torch.html#torch.prod" title="torch.prod"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.prod()</span></code></a></p></td>
<td><p><a class="reference internal" href="#removes-dimensions-doc"><span class="std std-ref">Removes dimensions</span></a></p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="torch.html#torch.rand" title="torch.rand"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.rand()</span></code></a></p></td>
<td><p><a class="reference internal" href="#factory-doc"><span class="std std-ref">Factory functions</span></a></p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="torch.html#torch.rand" title="torch.rand"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.rand()</span></code></a></p></td>
<td><p><a class="reference internal" href="#factory-doc"><span class="std std-ref">Factory functions</span></a></p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="torch.html#torch.randn" title="torch.randn"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.randn()</span></code></a></p></td>
<td><p><a class="reference internal" href="#factory-doc"><span class="std std-ref">Factory functions</span></a></p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="torch.html#torch.randn" title="torch.randn"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.randn()</span></code></a></p></td>
<td><p><a class="reference internal" href="#factory-doc"><span class="std std-ref">Factory functions</span></a></p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.random_" title="torch.Tensor.random_"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.random_()</span></code></a></p></td>
<td><p>None</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.reciprocal" title="torch.Tensor.reciprocal"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.reciprocal()</span></code></a>, <a class="reference internal" href="torch.html#torch.reciprocal" title="torch.reciprocal"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.reciprocal()</span></code></a></p></td>
<td><p><a class="reference internal" href="#keeps-input-names-doc"><span class="std std-ref">Keeps input names</span></a></p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.reciprocal_" title="torch.Tensor.reciprocal_"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.reciprocal_()</span></code></a></p></td>
<td><p>None</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="named_tensor.html#torch.Tensor.refine_names" title="torch.Tensor.refine_names"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.refine_names()</span></code></a></p></td>
<td><p>See documentation</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="autograd.html#torch.Tensor.register_hook" title="torch.Tensor.register_hook"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.register_hook()</span></code></a></p></td>
<td><p>None</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="named_tensor.html#torch.Tensor.rename" title="torch.Tensor.rename"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.rename()</span></code></a></p></td>
<td><p>See documentation</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="named_tensor.html#torch.Tensor.rename_" title="torch.Tensor.rename_"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.rename_()</span></code></a></p></td>
<td><p>See documentation</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="autograd.html#torch.Tensor.requires_grad" title="torch.Tensor.requires_grad"><code class="xref py py-attr docutils literal notranslate"><span class="pre">Tensor.requires_grad</span></code></a></p></td>
<td><p>None</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.requires_grad_" title="torch.Tensor.requires_grad_"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.requires_grad_()</span></code></a></p></td>
<td><p>None</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.resize_" title="torch.Tensor.resize_"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.resize_()</span></code></a></p></td>
<td><p>Only allow resizes that do not change shape</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.resize_as_" title="torch.Tensor.resize_as_"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.resize_as_()</span></code></a></p></td>
<td><p>Only allow resizes that do not change shape</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.round" title="torch.Tensor.round"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.round()</span></code></a>, <a class="reference internal" href="torch.html#torch.round" title="torch.round"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.round()</span></code></a></p></td>
<td><p><a class="reference internal" href="#keeps-input-names-doc"><span class="std std-ref">Keeps input names</span></a></p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.round_" title="torch.Tensor.round_"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.round_()</span></code></a></p></td>
<td><p>None</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.rsqrt" title="torch.Tensor.rsqrt"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.rsqrt()</span></code></a>, <a class="reference internal" href="torch.html#torch.rsqrt" title="torch.rsqrt"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.rsqrt()</span></code></a></p></td>
<td><p><a class="reference internal" href="#keeps-input-names-doc"><span class="std std-ref">Keeps input names</span></a></p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.rsqrt_" title="torch.Tensor.rsqrt_"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.rsqrt_()</span></code></a></p></td>
<td><p>None</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.select" title="torch.Tensor.select"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.select()</span></code></a>, <code class="xref py py-func docutils literal notranslate"><span class="pre">torch.select()</span></code></p></td>
<td><p><a class="reference internal" href="#removes-dimensions-doc"><span class="std std-ref">Removes dimensions</span></a></p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.short" title="torch.Tensor.short"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.short()</span></code></a></p></td>
<td><p><a class="reference internal" href="#keeps-input-names-doc"><span class="std std-ref">Keeps input names</span></a></p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.sigmoid" title="torch.Tensor.sigmoid"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.sigmoid()</span></code></a>, <a class="reference internal" href="torch.html#torch.sigmoid" title="torch.sigmoid"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.sigmoid()</span></code></a></p></td>
<td><p><a class="reference internal" href="#keeps-input-names-doc"><span class="std std-ref">Keeps input names</span></a></p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.sigmoid_" title="torch.Tensor.sigmoid_"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.sigmoid_()</span></code></a></p></td>
<td><p>None</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.sign" title="torch.Tensor.sign"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.sign()</span></code></a>, <a class="reference internal" href="torch.html#torch.sign" title="torch.sign"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.sign()</span></code></a></p></td>
<td><p><a class="reference internal" href="#keeps-input-names-doc"><span class="std std-ref">Keeps input names</span></a></p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.sign_" title="torch.Tensor.sign_"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.sign_()</span></code></a></p></td>
<td><p>None</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.sin" title="torch.Tensor.sin"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.sin()</span></code></a>, <a class="reference internal" href="torch.html#torch.sin" title="torch.sin"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.sin()</span></code></a></p></td>
<td><p><a class="reference internal" href="#keeps-input-names-doc"><span class="std std-ref">Keeps input names</span></a></p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.sin_" title="torch.Tensor.sin_"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.sin_()</span></code></a></p></td>
<td><p>None</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.sinh" title="torch.Tensor.sinh"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.sinh()</span></code></a>, <a class="reference internal" href="torch.html#torch.sinh" title="torch.sinh"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.sinh()</span></code></a></p></td>
<td><p><a class="reference internal" href="#keeps-input-names-doc"><span class="std std-ref">Keeps input names</span></a></p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.sinh_" title="torch.Tensor.sinh_"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.sinh_()</span></code></a></p></td>
<td><p>None</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.size" title="torch.Tensor.size"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.size()</span></code></a></p></td>
<td><p>None</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.split" title="torch.Tensor.split"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.split()</span></code></a>, <a class="reference internal" href="torch.html#torch.split" title="torch.split"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.split()</span></code></a></p></td>
<td><p><a class="reference internal" href="#keeps-input-names-doc"><span class="std std-ref">Keeps input names</span></a></p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.sqrt" title="torch.Tensor.sqrt"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.sqrt()</span></code></a>, <a class="reference internal" href="torch.html#torch.sqrt" title="torch.sqrt"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.sqrt()</span></code></a></p></td>
<td><p><a class="reference internal" href="#keeps-input-names-doc"><span class="std std-ref">Keeps input names</span></a></p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.sqrt_" title="torch.Tensor.sqrt_"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.sqrt_()</span></code></a></p></td>
<td><p>None</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.squeeze" title="torch.Tensor.squeeze"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.squeeze()</span></code></a>, <a class="reference internal" href="torch.html#torch.squeeze" title="torch.squeeze"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.squeeze()</span></code></a></p></td>
<td><p><a class="reference internal" href="#removes-dimensions-doc"><span class="std std-ref">Removes dimensions</span></a></p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.std" title="torch.Tensor.std"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.std()</span></code></a>, <a class="reference internal" href="torch.html#torch.std" title="torch.std"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.std()</span></code></a></p></td>
<td><p><a class="reference internal" href="#removes-dimensions-doc"><span class="std std-ref">Removes dimensions</span></a></p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="torch.html#torch.std_mean" title="torch.std_mean"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.std_mean()</span></code></a></p></td>
<td><p><a class="reference internal" href="#removes-dimensions-doc"><span class="std std-ref">Removes dimensions</span></a></p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.stride" title="torch.Tensor.stride"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.stride()</span></code></a></p></td>
<td><p>None</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.sub" title="torch.Tensor.sub"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.sub()</span></code></a>, <code class="xref py py-func docutils literal notranslate"><span class="pre">torch.sub()</span></code></p></td>
<td><p><a class="reference internal" href="#unifies-names-from-inputs-doc"><span class="std std-ref">Unifies names from inputs</span></a></p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.sub_" title="torch.Tensor.sub_"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.sub_()</span></code></a></p></td>
<td><p><a class="reference internal" href="#unifies-names-from-inputs-doc"><span class="std std-ref">Unifies names from inputs</span></a></p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.sum" title="torch.Tensor.sum"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.sum()</span></code></a>, <a class="reference internal" href="torch.html#torch.sum" title="torch.sum"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.sum()</span></code></a></p></td>
<td><p><a class="reference internal" href="#removes-dimensions-doc"><span class="std std-ref">Removes dimensions</span></a></p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.tan" title="torch.Tensor.tan"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.tan()</span></code></a>, <a class="reference internal" href="torch.html#torch.tan" title="torch.tan"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.tan()</span></code></a></p></td>
<td><p><a class="reference internal" href="#keeps-input-names-doc"><span class="std std-ref">Keeps input names</span></a></p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.tan_" title="torch.Tensor.tan_"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.tan_()</span></code></a></p></td>
<td><p>None</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.tanh" title="torch.Tensor.tanh"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.tanh()</span></code></a>, <a class="reference internal" href="torch.html#torch.tanh" title="torch.tanh"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.tanh()</span></code></a></p></td>
<td><p><a class="reference internal" href="#keeps-input-names-doc"><span class="std std-ref">Keeps input names</span></a></p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.tanh_" title="torch.Tensor.tanh_"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.tanh_()</span></code></a></p></td>
<td><p>None</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="torch.html#torch.tensor" title="torch.tensor"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.tensor()</span></code></a></p></td>
<td><p><a class="reference internal" href="#factory-doc"><span class="std std-ref">Factory functions</span></a></p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.to" title="torch.Tensor.to"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.to()</span></code></a></p></td>
<td><p><a class="reference internal" href="#keeps-input-names-doc"><span class="std std-ref">Keeps input names</span></a></p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.topk" title="torch.Tensor.topk"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.topk()</span></code></a>, <a class="reference internal" href="torch.html#torch.topk" title="torch.topk"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.topk()</span></code></a></p></td>
<td><p><a class="reference internal" href="#removes-dimensions-doc"><span class="std std-ref">Removes dimensions</span></a></p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.transpose" title="torch.Tensor.transpose"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.transpose()</span></code></a>, <a class="reference internal" href="torch.html#torch.transpose" title="torch.transpose"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.transpose()</span></code></a></p></td>
<td><p><a class="reference internal" href="#permutes-dimensions-doc"><span class="std std-ref">Permutes dimensions</span></a></p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.trunc" title="torch.Tensor.trunc"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.trunc()</span></code></a>, <a class="reference internal" href="torch.html#torch.trunc" title="torch.trunc"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.trunc()</span></code></a></p></td>
<td><p><a class="reference internal" href="#keeps-input-names-doc"><span class="std std-ref">Keeps input names</span></a></p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.trunc_" title="torch.Tensor.trunc_"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.trunc_()</span></code></a></p></td>
<td><p>None</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.type" title="torch.Tensor.type"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.type()</span></code></a></p></td>
<td><p>None</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.type_as" title="torch.Tensor.type_as"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.type_as()</span></code></a></p></td>
<td><p><a class="reference internal" href="#keeps-input-names-doc"><span class="std std-ref">Keeps input names</span></a></p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.unbind" title="torch.Tensor.unbind"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.unbind()</span></code></a>, <a class="reference internal" href="torch.html#torch.unbind" title="torch.unbind"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.unbind()</span></code></a></p></td>
<td><p><a class="reference internal" href="#removes-dimensions-doc"><span class="std std-ref">Removes dimensions</span></a></p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="named_tensor.html#torch.Tensor.unflatten" title="torch.Tensor.unflatten"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.unflatten()</span></code></a></p></td>
<td><p>See documentation</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.uniform_" title="torch.Tensor.uniform_"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.uniform_()</span></code></a></p></td>
<td><p>None</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.var" title="torch.Tensor.var"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.var()</span></code></a>, <a class="reference internal" href="torch.html#torch.var" title="torch.var"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.var()</span></code></a></p></td>
<td><p><a class="reference internal" href="#removes-dimensions-doc"><span class="std std-ref">Removes dimensions</span></a></p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="torch.html#torch.var_mean" title="torch.var_mean"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.var_mean()</span></code></a></p></td>
<td><p><a class="reference internal" href="#removes-dimensions-doc"><span class="std std-ref">Removes dimensions</span></a></p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="tensors.html#torch.Tensor.zero_" title="torch.Tensor.zero_"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.zero_()</span></code></a></p></td>
<td><p>None</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="torch.html#torch.zeros" title="torch.zeros"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.zeros()</span></code></a></p></td>
<td><p><a class="reference internal" href="#factory-doc"><span class="std std-ref">Factory functions</span></a></p></td>
</tr>
</tbody>
</table>
<div class="section" id="keeps-input-names">
<span id="keeps-input-names-doc"></span><h2>Keeps input names<a class="headerlink" href="#keeps-input-names" title="Permalink to this headline">¶</a></h2>
<p>All pointwise unary functions follow this rule as well as some other unary functions.</p>
<ul class="simple">
<li><p>Check names: None</p></li>
<li><p>Propagate names: input tensor’s names are propagated to the output.</p></li>
</ul>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">x</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">randn</span><span class="p">(</span><span class="mi">3</span><span class="p">,</span> <span class="mi">3</span><span class="p">,</span> <span class="n">names</span><span class="o">=</span><span class="p">(</span><span class="s1">&#39;N&#39;</span><span class="p">,</span> <span class="s1">&#39;C&#39;</span><span class="p">))</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">x</span><span class="o">.</span><span class="n">abs</span><span class="p">()</span><span class="o">.</span><span class="n">names</span>
<span class="go">(&#39;N&#39;, &#39;C&#39;)</span>
</pre></div>
</div>
</div>
<div class="section" id="removes-dimensions">
<span id="removes-dimensions-doc"></span><h2>Removes dimensions<a class="headerlink" href="#removes-dimensions" title="Permalink to this headline">¶</a></h2>
<p>All reduction ops like <a class="reference internal" href="tensors.html#torch.Tensor.sum" title="torch.Tensor.sum"><code class="xref py py-meth docutils literal notranslate"><span class="pre">sum()</span></code></a> remove dimensions by reducing
over the desired dimensions. Other operations like <a class="reference internal" href="tensors.html#torch.Tensor.select" title="torch.Tensor.select"><code class="xref py py-meth docutils literal notranslate"><span class="pre">select()</span></code></a> and
<a class="reference internal" href="tensors.html#torch.Tensor.squeeze" title="torch.Tensor.squeeze"><code class="xref py py-meth docutils literal notranslate"><span class="pre">squeeze()</span></code></a> remove dimensions.</p>
<p>Wherever one can pass an integer dimension index to an operator, one can also pass
a dimension name. Functions that take lists of dimension indices can also take in a
list of dimension names.</p>
<ul class="simple">
<li><p>Check names: If <code class="xref py py-attr docutils literal notranslate"><span class="pre">dim</span></code> or <code class="xref py py-attr docutils literal notranslate"><span class="pre">dims</span></code> is passed in as a list of names,
check that those names exist in <code class="xref py py-attr docutils literal notranslate"><span class="pre">self</span></code>.</p></li>
<li><p>Propagate names: If the dimensions of the input tensor specified by <code class="xref py py-attr docutils literal notranslate"><span class="pre">dim</span></code>
or <code class="xref py py-attr docutils literal notranslate"><span class="pre">dims</span></code> are not present in the output tensor, then the corresponding names
of those dimensions do not appear in <code class="docutils literal notranslate"><span class="pre">output.names</span></code>.</p></li>
</ul>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">x</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">randn</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="mi">3</span><span class="p">,</span> <span class="mi">3</span><span class="p">,</span> <span class="mi">3</span><span class="p">,</span> <span class="n">names</span><span class="o">=</span><span class="p">(</span><span class="s1">&#39;N&#39;</span><span class="p">,</span> <span class="s1">&#39;C&#39;</span><span class="p">,</span> <span class="s1">&#39;H&#39;</span><span class="p">,</span> <span class="s1">&#39;W&#39;</span><span class="p">))</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">x</span><span class="o">.</span><span class="n">squeeze</span><span class="p">(</span><span class="s1">&#39;N&#39;</span><span class="p">)</span><span class="o">.</span><span class="n">names</span>
<span class="go">(&#39;C&#39;, &#39;H&#39;, &#39;W&#39;)</span>

<span class="gp">&gt;&gt;&gt; </span><span class="n">x</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">randn</span><span class="p">(</span><span class="mi">3</span><span class="p">,</span> <span class="mi">3</span><span class="p">,</span> <span class="mi">3</span><span class="p">,</span> <span class="mi">3</span><span class="p">,</span> <span class="n">names</span><span class="o">=</span><span class="p">(</span><span class="s1">&#39;N&#39;</span><span class="p">,</span> <span class="s1">&#39;C&#39;</span><span class="p">,</span> <span class="s1">&#39;H&#39;</span><span class="p">,</span> <span class="s1">&#39;W&#39;</span><span class="p">))</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">x</span><span class="o">.</span><span class="n">sum</span><span class="p">([</span><span class="s1">&#39;N&#39;</span><span class="p">,</span> <span class="s1">&#39;C&#39;</span><span class="p">])</span><span class="o">.</span><span class="n">names</span>
<span class="go">(&#39;H&#39;, &#39;W&#39;)</span>

<span class="go"># Reduction ops with keepdim=True don&#39;t actually remove dimensions.</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">x</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">randn</span><span class="p">(</span><span class="mi">3</span><span class="p">,</span> <span class="mi">3</span><span class="p">,</span> <span class="mi">3</span><span class="p">,</span> <span class="mi">3</span><span class="p">,</span> <span class="n">names</span><span class="o">=</span><span class="p">(</span><span class="s1">&#39;N&#39;</span><span class="p">,</span> <span class="s1">&#39;C&#39;</span><span class="p">,</span> <span class="s1">&#39;H&#39;</span><span class="p">,</span> <span class="s1">&#39;W&#39;</span><span class="p">))</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">x</span><span class="o">.</span><span class="n">sum</span><span class="p">([</span><span class="s1">&#39;N&#39;</span><span class="p">,</span> <span class="s1">&#39;C&#39;</span><span class="p">],</span> <span class="n">keepdim</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span><span class="o">.</span><span class="n">names</span>
<span class="go">(&#39;N&#39;, &#39;C&#39;, &#39;H&#39;, &#39;W&#39;)</span>
</pre></div>
</div>
</div>
<div class="section" id="unifies-names-from-inputs">
<span id="unifies-names-from-inputs-doc"></span><h2>Unifies names from inputs<a class="headerlink" href="#unifies-names-from-inputs" title="Permalink to this headline">¶</a></h2>
<p>All binary arithmetic ops follow this rule. Operations that broadcast still
broadcast positionally from the right to preserve compatibility with unnamed
tensors. To perform explicit broadcasting by names, use <a class="reference internal" href="named_tensor.html#torch.Tensor.align_as" title="torch.Tensor.align_as"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.align_as()</span></code></a>.</p>
<ul class="simple">
<li><p>Check names: All names must match positionally from the right. i.e., in
<code class="docutils literal notranslate"><span class="pre">tensor</span> <span class="pre">+</span> <span class="pre">other</span></code>, <code class="docutils literal notranslate"><span class="pre">match(tensor.names[i],</span> <span class="pre">other.names[i])</span></code> must be true for all
<code class="docutils literal notranslate"><span class="pre">i</span></code> in <code class="docutils literal notranslate"><span class="pre">(-min(tensor.dim(),</span> <span class="pre">other.dim())</span> <span class="pre">+</span> <span class="pre">1,</span> <span class="pre">-1]</span></code>.</p></li>
<li><p>Check names: Furthermore, all named dimensions must be aligned from the right.
During matching, if we match a named dimension <code class="docutils literal notranslate"><span class="pre">A</span></code> with an unnamed dimension
<code class="docutils literal notranslate"><span class="pre">None</span></code>, then <code class="docutils literal notranslate"><span class="pre">A</span></code> must not appear in the tensor with the unnamed dimension.</p></li>
<li><p>Propagate names: unify pairs of names from the right from both tensors to
produce output names.</p></li>
</ul>
<p>For example,</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="c1"># tensor: Tensor[   N, None]</span>
<span class="c1"># other:  Tensor[None,    C]</span>
<span class="o">&gt;&gt;&gt;</span> <span class="n">tensor</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">randn</span><span class="p">(</span><span class="mi">3</span><span class="p">,</span> <span class="mi">3</span><span class="p">,</span> <span class="n">names</span><span class="o">=</span><span class="p">(</span><span class="s1">&#39;N&#39;</span><span class="p">,</span> <span class="kc">None</span><span class="p">))</span>
<span class="o">&gt;&gt;&gt;</span> <span class="n">other</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">randn</span><span class="p">(</span><span class="mi">3</span><span class="p">,</span> <span class="mi">3</span><span class="p">,</span> <span class="n">names</span><span class="o">=</span><span class="p">(</span><span class="kc">None</span><span class="p">,</span> <span class="s1">&#39;C&#39;</span><span class="p">))</span>
<span class="o">&gt;&gt;&gt;</span> <span class="p">(</span><span class="n">tensor</span> <span class="o">+</span> <span class="n">other</span><span class="p">)</span><span class="o">.</span><span class="n">names</span>
<span class="p">(</span><span class="s1">&#39;N&#39;</span><span class="p">,</span> <span class="s1">&#39;C&#39;</span><span class="p">)</span>
</pre></div>
</div>
<p>Check names:</p>
<ul class="simple">
<li><p><code class="docutils literal notranslate"><span class="pre">match(tensor.names[-1],</span> <span class="pre">other.names[-1])</span></code> is <code class="docutils literal notranslate"><span class="pre">True</span></code></p></li>
<li><p><code class="docutils literal notranslate"><span class="pre">match(tensor.names[-2],</span> <span class="pre">tensor.names[-2])</span></code> is <code class="docutils literal notranslate"><span class="pre">True</span></code></p></li>
<li><p>Because we matched <code class="docutils literal notranslate"><span class="pre">None</span></code> in <a class="reference internal" href="torch.html#torch.tensor" title="torch.tensor"><code class="xref py py-attr docutils literal notranslate"><span class="pre">tensor</span></code></a> with <code class="docutils literal notranslate"><span class="pre">'C'</span></code>,
check to make sure <code class="docutils literal notranslate"><span class="pre">'C'</span></code> doesn’t exist in <a class="reference internal" href="torch.html#torch.tensor" title="torch.tensor"><code class="xref py py-attr docutils literal notranslate"><span class="pre">tensor</span></code></a> (it does not).</p></li>
<li><p>Check to make sure <code class="docutils literal notranslate"><span class="pre">'N'</span></code> doesn’t exists in <code class="xref py py-attr docutils literal notranslate"><span class="pre">other</span></code> (it does not).</p></li>
</ul>
<p>Finally, the output names are computed with
<code class="docutils literal notranslate"><span class="pre">[unify('N',</span> <span class="pre">None),</span> <span class="pre">unify(None,</span> <span class="pre">'C')]</span> <span class="pre">=</span> <span class="pre">['N',</span> <span class="pre">'C']</span></code></p>
<p>More examples:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="c1"># Dimensions don&#39;t match from the right:</span>
<span class="c1"># tensor: Tensor[N, C]</span>
<span class="c1"># other:  Tensor[   N]</span>
<span class="o">&gt;&gt;&gt;</span> <span class="n">tensor</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">randn</span><span class="p">(</span><span class="mi">3</span><span class="p">,</span> <span class="mi">3</span><span class="p">,</span> <span class="n">names</span><span class="o">=</span><span class="p">(</span><span class="s1">&#39;N&#39;</span><span class="p">,</span> <span class="s1">&#39;C&#39;</span><span class="p">))</span>
<span class="o">&gt;&gt;&gt;</span> <span class="n">other</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">randn</span><span class="p">(</span><span class="mi">3</span><span class="p">,</span> <span class="n">names</span><span class="o">=</span><span class="p">(</span><span class="s1">&#39;N&#39;</span><span class="p">,))</span>
<span class="o">&gt;&gt;&gt;</span> <span class="p">(</span><span class="n">tensor</span> <span class="o">+</span> <span class="n">other</span><span class="p">)</span><span class="o">.</span><span class="n">names</span>
<span class="ne">RuntimeError</span><span class="p">:</span> <span class="n">Error</span> <span class="n">when</span> <span class="n">attempting</span> <span class="n">to</span> <span class="n">broadcast</span> <span class="n">dims</span> <span class="p">[</span><span class="s1">&#39;N&#39;</span><span class="p">,</span> <span class="s1">&#39;C&#39;</span><span class="p">]</span> <span class="ow">and</span> <span class="n">dims</span>
<span class="p">[</span><span class="s1">&#39;N&#39;</span><span class="p">]:</span> <span class="n">dim</span> <span class="s1">&#39;C&#39;</span> <span class="ow">and</span> <span class="n">dim</span> <span class="s1">&#39;N&#39;</span> <span class="n">are</span> <span class="n">at</span> <span class="n">the</span> <span class="n">same</span> <span class="n">position</span> <span class="kn">from</span> <span class="nn">the</span> <span class="n">right</span> <span class="n">but</span> <span class="n">do</span>
<span class="ow">not</span> <span class="n">match</span><span class="o">.</span>

<span class="c1"># Dimensions aren&#39;t aligned when matching tensor.names[-1] and other.names[-1]:</span>
<span class="c1"># tensor: Tensor[N, None]</span>
<span class="c1"># other:  Tensor[      N]</span>
<span class="o">&gt;&gt;&gt;</span> <span class="n">tensor</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">randn</span><span class="p">(</span><span class="mi">3</span><span class="p">,</span> <span class="mi">3</span><span class="p">,</span> <span class="n">names</span><span class="o">=</span><span class="p">(</span><span class="s1">&#39;N&#39;</span><span class="p">,</span> <span class="kc">None</span><span class="p">))</span>
<span class="o">&gt;&gt;&gt;</span> <span class="n">other</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">randn</span><span class="p">(</span><span class="mi">3</span><span class="p">,</span> <span class="n">names</span><span class="o">=</span><span class="p">(</span><span class="s1">&#39;N&#39;</span><span class="p">,))</span>
<span class="o">&gt;&gt;&gt;</span> <span class="p">(</span><span class="n">tensor</span> <span class="o">+</span> <span class="n">other</span><span class="p">)</span><span class="o">.</span><span class="n">names</span>
<span class="ne">RuntimeError</span><span class="p">:</span> <span class="n">Misaligned</span> <span class="n">dims</span> <span class="n">when</span> <span class="n">attempting</span> <span class="n">to</span> <span class="n">broadcast</span> <span class="n">dims</span> <span class="p">[</span><span class="s1">&#39;N&#39;</span><span class="p">]</span> <span class="ow">and</span>
<span class="n">dims</span> <span class="p">[</span><span class="s1">&#39;N&#39;</span><span class="p">,</span> <span class="kc">None</span><span class="p">]:</span> <span class="n">dim</span> <span class="s1">&#39;N&#39;</span> <span class="n">appears</span> <span class="ow">in</span> <span class="n">a</span> <span class="n">different</span> <span class="n">position</span> <span class="kn">from</span> <span class="nn">the</span> <span class="n">right</span>
<span class="n">across</span> <span class="n">both</span> <span class="n">lists</span><span class="o">.</span>
</pre></div>
</div>
<div class="admonition note">
<p class="admonition-title">Note</p>
<p>In both of the last examples, it is possible to align the tensors by names
and then perform the addition. Use <a class="reference internal" href="named_tensor.html#torch.Tensor.align_as" title="torch.Tensor.align_as"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.align_as()</span></code></a> to align
tensors by name or <a class="reference internal" href="named_tensor.html#torch.Tensor.align_to" title="torch.Tensor.align_to"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.align_to()</span></code></a> to align tensors to a custom
dimension ordering.</p>
</div>
</div>
<div class="section" id="permutes-dimensions">
<span id="permutes-dimensions-doc"></span><h2>Permutes dimensions<a class="headerlink" href="#permutes-dimensions" title="Permalink to this headline">¶</a></h2>
<p>Some operations, like <a class="reference internal" href="tensors.html#torch.Tensor.t" title="torch.Tensor.t"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Tensor.t()</span></code></a>, permute the order of dimensions. Dimension names
are attached to individual dimensions so they get permuted as well.</p>
<p>If the operator takes in positional index <code class="xref py py-attr docutils literal notranslate"><span class="pre">dim</span></code>, it is also able to take a dimension
name as <code class="xref py py-attr docutils literal notranslate"><span class="pre">dim</span></code>.</p>
<ul class="simple">
<li><p>Check names: If <code class="xref py py-attr docutils literal notranslate"><span class="pre">dim</span></code> is passed as a name, check that it exists in the tensor.</p></li>
<li><p>Propagate names: Permute dimension names in the same way as the dimensions that are
being permuted.</p></li>
</ul>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">x</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">randn</span><span class="p">(</span><span class="mi">3</span><span class="p">,</span> <span class="mi">3</span><span class="p">,</span> <span class="n">names</span><span class="o">=</span><span class="p">(</span><span class="s1">&#39;N&#39;</span><span class="p">,</span> <span class="s1">&#39;C&#39;</span><span class="p">))</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">x</span><span class="o">.</span><span class="n">transpose</span><span class="p">(</span><span class="s1">&#39;N&#39;</span><span class="p">,</span> <span class="s1">&#39;C&#39;</span><span class="p">)</span><span class="o">.</span><span class="n">names</span>
<span class="go">(&#39;C&#39;, &#39;N&#39;)</span>
</pre></div>
</div>
</div>
<div class="section" id="contracts-away-dims">
<span id="contracts-away-dims-doc"></span><h2>Contracts away dims<a class="headerlink" href="#contracts-away-dims" title="Permalink to this headline">¶</a></h2>
<p>Matrix multiply functions follow some variant of this. Let’s go through
<a class="reference internal" href="torch.html#torch.mm" title="torch.mm"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.mm()</span></code></a> first and then generalize the rule for batch matrix multiplication.</p>
<p>For <code class="docutils literal notranslate"><span class="pre">torch.mm(tensor,</span> <span class="pre">other)</span></code>:</p>
<ul class="simple">
<li><p>Check names: None</p></li>
<li><p>Propagate names: result names are <code class="docutils literal notranslate"><span class="pre">(tensor.names[-2],</span> <span class="pre">other.names[-1])</span></code>.</p></li>
</ul>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">x</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">randn</span><span class="p">(</span><span class="mi">3</span><span class="p">,</span> <span class="mi">3</span><span class="p">,</span> <span class="n">names</span><span class="o">=</span><span class="p">(</span><span class="s1">&#39;N&#39;</span><span class="p">,</span> <span class="s1">&#39;D&#39;</span><span class="p">))</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">y</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">randn</span><span class="p">(</span><span class="mi">3</span><span class="p">,</span> <span class="mi">3</span><span class="p">,</span> <span class="n">names</span><span class="o">=</span><span class="p">(</span><span class="s1">&#39;in&#39;</span><span class="p">,</span> <span class="s1">&#39;out&#39;</span><span class="p">))</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">x</span><span class="o">.</span><span class="n">mm</span><span class="p">(</span><span class="n">y</span><span class="p">)</span><span class="o">.</span><span class="n">names</span>
<span class="go">(&#39;N&#39;, &#39;out&#39;)</span>
</pre></div>
</div>
<p>Inherently, a matrix multiplication performs a dot product over two dimensions,
collapsing them. When two tensors are matrix-multiplied, the contracted dimensions
disappear and do not show up in the output tensor.</p>
<p><a class="reference internal" href="torch.html#torch.mv" title="torch.mv"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.mv()</span></code></a>, <a class="reference internal" href="torch.html#torch.dot" title="torch.dot"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.dot()</span></code></a> work in a similar way: name inference does not
check input names and removes the dimensions that are involved in the dot product:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">x</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">randn</span><span class="p">(</span><span class="mi">3</span><span class="p">,</span> <span class="mi">3</span><span class="p">,</span> <span class="n">names</span><span class="o">=</span><span class="p">(</span><span class="s1">&#39;N&#39;</span><span class="p">,</span> <span class="s1">&#39;D&#39;</span><span class="p">))</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">y</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">randn</span><span class="p">(</span><span class="mi">3</span><span class="p">,</span> <span class="n">names</span><span class="o">=</span><span class="p">(</span><span class="s1">&#39;something&#39;</span><span class="p">,))</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">x</span><span class="o">.</span><span class="n">mv</span><span class="p">(</span><span class="n">y</span><span class="p">)</span><span class="o">.</span><span class="n">names</span>
<span class="go">(&#39;N&#39;,)</span>
</pre></div>
</div>
<p>Now, let’s take a look at <code class="docutils literal notranslate"><span class="pre">torch.matmul(tensor,</span> <span class="pre">other)</span></code>. Assume that <code class="docutils literal notranslate"><span class="pre">tensor.dim()</span> <span class="pre">&gt;=</span> <span class="pre">2</span></code>
and <code class="docutils literal notranslate"><span class="pre">other.dim()</span> <span class="pre">&gt;=</span> <span class="pre">2</span></code>.</p>
<ul class="simple">
<li><p>Check names: Check that the batch dimensions of the inputs are aligned and broadcastable.
See <a class="reference internal" href="#unifies-names-from-inputs-doc"><span class="std std-ref">Unifies names from inputs</span></a> for what it means for the inputs to be aligned.</p></li>
<li><p>Propagate names: result names are obtained by unifying the batch dimensions and removing
the contracted dimensions:
<code class="docutils literal notranslate"><span class="pre">unify(tensor.names[:-2],</span> <span class="pre">other.names[:-2])</span> <span class="pre">+</span> <span class="pre">(tensor.names[-2],</span> <span class="pre">other.names[-1])</span></code>.</p></li>
</ul>
<p>Examples:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="c1"># Batch matrix multiply of matrices Tensor[&#39;C&#39;, &#39;D&#39;] and Tensor[&#39;E&#39;, &#39;F&#39;].</span>
<span class="c1"># &#39;A&#39;, &#39;B&#39; are batch dimensions.</span>
<span class="o">&gt;&gt;&gt;</span> <span class="n">x</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">randn</span><span class="p">(</span><span class="mi">3</span><span class="p">,</span> <span class="mi">3</span><span class="p">,</span> <span class="mi">3</span><span class="p">,</span> <span class="mi">3</span><span class="p">,</span> <span class="n">names</span><span class="o">=</span><span class="p">(</span><span class="s1">&#39;A&#39;</span><span class="p">,</span> <span class="s1">&#39;B&#39;</span><span class="p">,</span> <span class="s1">&#39;C&#39;</span><span class="p">,</span> <span class="s1">&#39;D&#39;</span><span class="p">))</span>
<span class="o">&gt;&gt;&gt;</span> <span class="n">y</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">randn</span><span class="p">(</span><span class="mi">3</span><span class="p">,</span> <span class="mi">3</span><span class="p">,</span> <span class="mi">3</span><span class="p">,</span> <span class="n">names</span><span class="o">=</span><span class="p">(</span><span class="s1">&#39;B&#39;</span><span class="p">,</span> <span class="s1">&#39;E&#39;</span><span class="p">,</span> <span class="s1">&#39;F&#39;</span><span class="p">))</span>
<span class="o">&gt;&gt;&gt;</span> <span class="n">torch</span><span class="o">.</span><span class="n">matmul</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="n">y</span><span class="p">)</span><span class="o">.</span><span class="n">names</span>
<span class="p">(</span><span class="s1">&#39;A&#39;</span><span class="p">,</span> <span class="s1">&#39;B&#39;</span><span class="p">,</span> <span class="s1">&#39;C&#39;</span><span class="p">,</span> <span class="s1">&#39;F&#39;</span><span class="p">)</span>
</pre></div>
</div>
<p>Finally, there are fused <code class="docutils literal notranslate"><span class="pre">add</span></code> versions of many matmul functions. i.e., <a class="reference internal" href="torch.html#torch.addmm" title="torch.addmm"><code class="xref py py-func docutils literal notranslate"><span class="pre">addmm()</span></code></a>
and <a class="reference internal" href="torch.html#torch.addmv" title="torch.addmv"><code class="xref py py-func docutils literal notranslate"><span class="pre">addmv()</span></code></a>. These are treated as composing name inference for i.e. <a class="reference internal" href="torch.html#torch.mm" title="torch.mm"><code class="xref py py-func docutils literal notranslate"><span class="pre">mm()</span></code></a> and
name inference for <a class="reference internal" href="torch.html#torch.add" title="torch.add"><code class="xref py py-func docutils literal notranslate"><span class="pre">add()</span></code></a>.</p>
</div>
<div class="section" id="factory-functions">
<span id="factory-doc"></span><h2>Factory functions<a class="headerlink" href="#factory-functions" title="Permalink to this headline">¶</a></h2>
<p>Factory functions now take a new <code class="xref py py-attr docutils literal notranslate"><span class="pre">names</span></code> argument that associates a name
with each dimension.</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">torch</span><span class="o">.</span><span class="n">zeros</span><span class="p">(</span><span class="mi">2</span><span class="p">,</span> <span class="mi">3</span><span class="p">,</span> <span class="n">names</span><span class="o">=</span><span class="p">(</span><span class="s1">&#39;N&#39;</span><span class="p">,</span> <span class="s1">&#39;C&#39;</span><span class="p">))</span>
<span class="go">tensor([[0., 0., 0.],</span>
<span class="go">        [0., 0., 0.]], names=(&#39;N&#39;, &#39;C&#39;))</span>
</pre></div>
</div>
</div>
<div class="section" id="out-function-and-in-place-variants">
<span id="out-function-semantics-doc"></span><h2>out function and in-place variants<a class="headerlink" href="#out-function-and-in-place-variants" title="Permalink to this headline">¶</a></h2>
<p>A tensor specified as an <code class="docutils literal notranslate"><span class="pre">out=</span></code> tensor has the following behavior:</p>
<ul class="simple">
<li><p>If it has no named dimensions, then the names computed from the operation
get propagated to it.</p></li>
<li><p>If it has any named dimensions, then the names computed from the operation
must be exactly equal to the existing names. Otherwise, the operation errors.</p></li>
</ul>
<p>All in-place methods modify inputs to have names equal to the computed names
from name inference. For example,</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">x</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">randn</span><span class="p">(</span><span class="mi">3</span><span class="p">,</span> <span class="mi">3</span><span class="p">)</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">y</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">randn</span><span class="p">(</span><span class="mi">3</span><span class="p">,</span> <span class="mi">3</span><span class="p">,</span> <span class="n">names</span><span class="o">=</span><span class="p">(</span><span class="s1">&#39;N&#39;</span><span class="p">,</span> <span class="s1">&#39;C&#39;</span><span class="p">))</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">x</span><span class="o">.</span><span class="n">names</span>
<span class="go">(None, None)</span>

<span class="gp">&gt;&gt;&gt; </span><span class="n">x</span> <span class="o">+=</span> <span class="n">y</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">x</span><span class="o">.</span><span class="n">names</span>
<span class="go">(&#39;N&#39;, &#39;C&#39;)</span>
</pre></div>
</div>
</div>
</div>


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